1. Field of the Invention
The present invention relates to magnetic storage systems. More particularly, the present invention relates to a system and a method for reliably and accurately optimizing readback channel parameters of a magnetic storage system.
2. Description of the Related Art
FIG. 1 shows a functional block diagram of an exemplary magnetic tape recording system 100 that is connected to a host system 101. Magnetic tape recording system 100 includes read and write circuitry 102, a transducer 103, and a magnetic tape 104. Magnetic tape 104 is contained in a cartridge 105 and is taken up on a take-up reel 106 as magnetic tape 104 is transported past transducer 103. Binary data from host system 101 is stored on magnetic tape 104 by the write portion of read and write circuitry 102 selectively orienting magnetization in user data fields in the magnetic media of magnetic tape 104.
FIG. 2 shows a functional block diagram of the major functional blocks of an exemplary magnetic recording system 200 that is part of a magnetic tape recording system, such as magnetic tape recording system 100 shown in FIG. 1. Recording system 200 includes a write channel portion and a readback channel portion. The write channel portion includes a write formatter 202, a write driver 203 and a write head 204. During a recording operation, binary data 201 that is to be stored on a magnetic medium, such as magnetic tape 104, is input to write formatter 202. Write formatter 202, depending on the implementation, may add extra transitions between data transitions in a process referred to in the art as “write equalization.” Write formatter 202 may also shift write pulses in time with respect to a write clock in a well-known manner, known in the art as “write precompensation,” to improve recording performance of binary data 201. The output of write formatter 202 is applied to write driver 203, which, in turn is coupled to write head 204. Write head 204 writes binary data 201 onto the surface of magnetic media 205 in a well-known manner.
The readback channel portion of recording system 200 includes an analog readback channel 206 and a digital readback channel 210. Analog read channel 206 includes a read head 207, a read amplifier 208 and an Automatic Gain Control (AGC) system 209. Digital read channel 210 includes an Analog-to-Digital (A/D) converter 211, an equalizer filter system 212, a timing recovery system 213 and a data detector 214.
During a read operation, read head 207 detects stored data from magnetic media 205 and generates a readback signal that is amplified by read amplifier 208. The gain of read amplifier 208 is controlled by AGC system 209 and the output of AGC system 209 is input to digital readback channel 210. A/D converter 211 digitizes the output of AGC system 209. The output of AID converter 211 passes through equalizer filter system 212 and timing recovery system 213 before being applied to data detector 214. Data Detector 214 outputs the stored binary data 215 that was detected by read head 207 as the readback signal.
The task of the readback channel portion of recording system 200 is to properly decode the written data from the readback signal in the presence of a number of impairments, such as noise, variations in the media velocity, and variations of the head/media transfer function. Variations in the media velocity require that the clock of the readback system be continuously synchronized with the bits written on the magnetic medium by frequent updates to the period and phase of the readback system clock using an error signal that is based on the random data contained in the user data fields. For synchronous-sampling-type systems, the timing recovery feedback loop synchronizes the clock of the analog-to-digital converter. See, for example, R. D. Cideciyan et al., “A PRML System for Digital Magnetic Recording,” IEEE Journal on Selected Areas in Communications, Vol. 10, No. 1, pp. 38–56, (1992). In asynchronous-sampling-type systems, the timing recovery feedback loop adjusts the phase of the synchronous sample interpolator. See, for example, U.S. Pat. No. 6,084,924 to C.M. Melas.
Variations in the head/media transfer function require repeated updating of many of the readback channel parameters. For example, the gain of read amplifier 208 must be continuously adjusted to compensate for variations in the head/media spacing, defects on the media surface or in the media itself, and variations in the signal amplitude. Additionally, the overall gain through the readback channel is constantly adjusted by an AGC operation that is performed in the analog domain, such as by AGC system 209, and in the digital domain within digital readback channel 210 using data decisions (not shown). AGC system 209 is a variable gain block that ensures that the amplitude of the signal envelope of the readback stays within prescribed boundaries. The gain control provided by AGC system 209 is conventionally determined by measuring the maximum value of the readback signal within a defined time window and then appropriately adjusting the maximum value to be within the prescribed boundaries. A conventional AGC block for a readback channel operates on the assumption that the random user data signal contains some isolated transitions having the maximum voltage swing. To ensure that this assumption is true, the random user data is conventionally encoded before being written to the magnetic medium. The AGC function of digital readback channel 210 receives an error signal from a data estimator (not shown in FIG. 2) that is the difference between a target signal value, received from the data estimator, and the actual value. The data estimator for the AGC and the timing loops is usually located between the timing recovery and the data detector.
Variations in the head/media transfer function also gives rise to a need for adaptive equalization, which is the process of changing or “adapting” the coefficients of equalizer filter system 212 which shape the readback channel transfer response to be a prescribed transfer function. The most common conventional adaptive equalization techniques utilize a Minimum Mean Square Error (MMSE) approach for continuously updating the coefficients of equalizer filter system 212. The adaptation is calculated based on an ideal, or target, sample value output of a data estimator and a comparison of the ideal sample value with a detected value. A data estimator can have many errors, and to ensure stability, equalizer adaptation is done very slowly using small updates, resulting in a slow convergence of a set of equalizer coefficients. Large levels of noise, however, can cause the adaptation algorithm to diverge.
All of the abovementioned channel parameter updates are conventionally based on the readback signal corresponding to the random user data stored on the magnetic medium as the readback signal is detected by the read head. Accordingly, the random data is estimated using a fast method and the estimates are used for setting the various control loops, such as timing recovery, AGC control and the adaptive equalization. When a fast estimation technique, such as a slicer, is used, very little noise can be tolerated before errors occur. When too many errors occur during the estimation process, the various control loops can become unstable, especially the timing control loop, resulting in very large blocks of errors. More reliable techniques of estimating the data introduce too much delay in the feedback loops. Thus, control loops that rely on data from a fast, but noisy estimator technique limit the level of noise in the system that can be tolerated by the read channel.
Consequently, what is needed is a technique for reliably and accurately optimizing timing recovery, AGC control and adaptive equalization of a readback channel.